Regression model for bearing capacity of a square footing on reinforced pond ash

• Published in: Geotextiles and geomembranes Vol. 23; no. 3; pp. 261 - 285
• Main Authors: Bera, Ashis Kumar, Ghosh, Ambarish, Ghosh, Amalendu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-06-2005
• Subjects: Bearing capacity; Geotextiles; Pond ash; Power model; Regression; Square footing; Regression; Square footing; Bearing capacity; Pond ash; Power model; Geotextiles
• ISSN: 0266-1144; 1879-3584
• DOI: 10.1016/j.geotexmem.2004.09.002

This paper presents the regression analysis of the bearing capacity of a square footing on reinforced pond ash. A power model has been developed to estimate bearing capacity of a square footing
(
q
rs
)
on reinforced pond ash at any settlement using all possible regression techniques based on 2088 model test data to select the significant subset of the predictors. From the regression analysis, the predictors viz., the bearing capacity of a square footing
(
q
s
)
at the same settlement on unreinforced pond ash, settlement to width of the footing ratio
(
s
/
B
)
in percentage, number of layers (
N) of reinforcement, friction ratio (
f), i.e. the ratio of the pond ash—geotextile interface friction angle (
ψ
) to the direct shear friction angle of pond ash
(
φ
d
)
, depth of the upper most layer of reinforcement from the base of the footing to width of the footing ratio
(
u
/
B
)
, length of reinforcement sheet to width of footing ratio
(
L
s
/
B
)
and vertical spacing of the reinforcement to width of the footing ratio
(
S
v
/
B
)
are found to be significant to the model. The adjusted coefficient of determination
(
R
adj
2
)
for the proposed model is found to be 0.9448 and for the regression model 72% data out of 2088 observed data have prediction with less than 15% error. The additional set of 99 data was used for validation of the model.